Home
Home   >   News&Events   >   Content

Data-driven Model Predictive Control: A Powerful New Approach for a Successful Control Method by Professor Frank Allgöwer

Time:November 16, 2022          Browse:

On November 11, 2022, the 43th Zhi·Xin forum of our college was held in the form of online Zoom meeting. Professor Frank Allgöwer from the University of Stuttgart was invited to give a talk titled “Data-driven Model Predictive Control: A Powerful New Approach for a Successful Control Method”.

First, Prof. Frank Allgöwer introduced the design method of feedback controllers in automatic control with an example of a bicycle. Then, model predictive control techniques were discussed by comparing analytical/numerical-based control methods, model predictive control problem formation and solution, and the basic principles of model predictive control were presented. After that, the difficulties of model-based control and the motivation for studying data-driven control were analyzed. In addition, Prof. Frank Allgöwer presented the data-driven model predictive control methods for linear systems in the absence and presence of noisy data in detail. Furthermore, he also introduced the practical applications of data-driven model predictive control methods for nonlinear systems, such as four-tank systems and soft robot systems. Finally, he analyzed many open research problems for data-driven model predictive control techniques in the future.

After the talk,Prof. Frank Allgöwer exchanged views with teachers and students on issues related to data-driven model predictive control. The talk further expanded the research horizons of our students and enhanced their understanding and knowledge of data-driven model predictive control techniques.

Written by Zhang Hao

Photographed by Wang Yunjiao

Pre:Interval Type-2 Fuzzy System and its Applications by Professor H. K. Lam

Next:"Recent Research on Intelligent Systems and Control" by Associate Professor LIU Lu

CLOSE

Contact us

Address: 4800 Cao'an Highway, Shanghai 201804, P. R. China

Zip code: 201804

Copyright© 2021  College of Electronic and Information Engineering, Tongji University